Reworking of Marcus’ code
Note that EQ subscales were not part of the original scale, but are based on Lawrence et al., 2004.
Run only the first time, before data sharing
data_trimmed <- data_raw %>%
rename(
# rename "Q" to PET, rename attention checks items
PET_1 = Q2,
PET_2 = Q4,
PET_3 = Q6,
PET_4 = Q8,
PET_5 = Q10,
PET_6 = Q12,
PET_7 = Q14,
attention_check_1 = IRI_24,
# Because of the attention check item, all IRI_items after 24 have to be renamed
IRI_24 = IRI_25,
IRI_25 = IRI_26,
IRI_26 = IRI_27,
IRI_27 = IRI_28,
IRI_28 = IRI_29,
attention_check_2 = EQ_60,
# Because of the attention check item, EQ Item 61 has to be renamed
EQ_60 = EQ_61,
PTTA_1 = PTT.A_test1,
PTTA_2 = PTT.A_test2,
PTTA_3 = PTT.A_test3,
PTTA_4 = PTT.A_test4,
PTTA_5 = PTT.A_test5,
PTTA_6 = PTT.A_test6,
PTTA_7 = PTT.A_test7,
PTTA_8 = PTT.A_test8,
PTTA_9 = PTT.A_test9,
PTTA_10 = PTT.A_test10,
PTTA_11 = PTT.A_test11,
PTTA_12 = PTT.A_test12,
PTTA_13 = PTT.A_test13,
PTTA_14 = PTT.A_test14,
PTTA_15 = PTT.A_test15,
PTTA_16 = PTT.A_test16,
PTTA_17 = PTT.A_test17,
PTTA_18 = PTT.A_test18,
PTTA_19 = PTT.A_test19,
PTTA_20 = PTT.A_test20,
PTTA_21 = PTT.A_test21,
PTTA_22 = PTT.A_test22,
PTTA_23 = PTT.A_test23,
PTTA_24 = PTT.A_test24,
PTTA_25 = PTT.A_test25,
PTTA_26 = PTT.A_test26,
PTTA_27 = PTT.A_test27,
PTTA_28 = PTT.A_test28,
PTTA_29 = PTT.A_test29,
PTTA_30 = PTT.A_test30,
PTTA_31 = PTT.A_test31,
PTTA_32 = PTT.A_test32
) |>
# wrangle gender
mutate(gender = ifelse(Gender == "self-identified:", Gender_3_TEXT, Gender)) |>
# select variables of interest
select(unique_id,
timepoint,
age = Age_1,
gender,
attention_check_1,
attention_check_2,
SITES,
starts_with("IRI_"),
starts_with("EQ_"),
starts_with("PET_"),
starts_with("EYES_"),
starts_with("PTP_"),
starts_with("PTTA_")) |>
# drop meta data columns
select(!ends_with(".Click") & !ends_with(".Submit") & !ends_with(".Count")) |>
# drop filler and sample items
select(!all_of(c("EYES_0",
"EQ_2", "EQ_3", "EQ_5", "EQ_7", "EQ_9", "EQ_13", "EQ_16", "EQ_17", "EQ_20", "EQ_23",
"EQ_24",
# "EQ_30", # is not used in the total score, but is used in the social skills subscale
# "EQ_31", # is not used in the total score, but is used in the social skills subscale
# "EQ_33", # is not used in the total score, but is used in the social skills subscale
"EQ_40", "EQ_45", "EQ_47",
# "EQ_51", # is not used in the total score, but is used in the social skills subscale
# "EQ_53", # is not used in the total score, but is used in the social skills subscale
"EQ_56"))) data_recoded <- data_trimmed |>
# age
mutate(age = as.numeric(age)) |>
# attention checks
mutate(attention_check_1 = ifelse(attention_check_1 == "C", "passed", "failed"),
attention_check_2 = ifelse(attention_check_2 == "strongly agree", "passed", "failed")) |>
# SITES
mutate(SITES = recode(SITES,
'1 Not very true of me' = 1,
'2' = 2,
'3' = 3,
'4' = 4,
'5 Very true of me.' = 5)) |>
# IRI
mutate(across(
all_of(c("IRI_1", "IRI_2", "IRI_5", "IRI_6", "IRI_8", "IRI_9", "IRI_10", "IRI_11", "IRI_16", "IRI_17",
"IRI_20", "IRI_21", "IRI_22", "IRI_23", "IRI_24", "IRI_25", "IRI_26", "IRI_27", "IRI_28")),
~ recode(.x,
'A - DOES NOT DESCRIBE ME VERY WELL' = 0,
'B' = 1,
'C' = 2,
'D' = 3,
'E - DESCRIBES ME VERY WELL' = 4)
)) |>
mutate(across(
all_of(c("IRI_3", "IRI_4", "IRI_7", "IRI_12", "IRI_13", "IRI_14", "IRI_15", "IRI_18", "IRI_19")),
~ recode(.x,
'A - DOES NOT DESCRIBE ME VERY WELL' = 4,
'B' = 3,
'C' = 2,
'D' = 1,
'E - DESCRIBES ME VERY WELL' = 0)
)) |>
# # EQ
# mutate(across(
# all_of(c("EQ_1", "EQ_6", "EQ_19", "EQ_22", "EQ_25", "EQ_26", "EQ_35", "EQ_36", "EQ_37", "EQ_38",
# "EQ_41", "EQ_42", "EQ_43", "EQ_44", "EQ_52", "EQ_54", "EQ_55", "EQ_57", "EQ_58", "EQ_59", "EQ_60")),
# ~ recode(.x,
# 'strongly agree' = 2,
# 'slightly agree' = 1,
# 'slightly disagree' = 0,
# 'strongly disagree' = 0)
# )) |>
# mutate(across(
# all_of(c("EQ_4", "EQ_8", "EQ_10", "EQ_11", "EQ_12", "EQ_14", "EQ_15", "EQ_18", "EQ_21", "EQ_27", "EQ_28",
# "EQ_29", "EQ_32", "EQ_34", "EQ_39", "EQ_46", "EQ_48", "EQ_49", "EQ_50")),
# ~ recode(.x,
# 'strongly agree' = 2,
# 'slightly agree' = 1,
# 'slightly disagree' = 0,
# 'strongly disagree' = 0)
# )) |>
# EQ
mutate(across(
all_of(c("EQ_1", "EQ_6", "EQ_19", "EQ_22", "EQ_25", "EQ_26", "EQ_35", "EQ_36", "EQ_37", "EQ_38",
"EQ_41", "EQ_42", "EQ_43", "EQ_44", "EQ_52", "EQ_54", "EQ_55", "EQ_57", "EQ_58", "EQ_59",
"EQ_60", "EQ_33", "EQ_51", "EQ_53")), # <-- added EQ_33, EQ_51, EQ_53
~ recode(.x,
'strongly agree' = 2,
'slightly agree' = 1,
'slightly disagree' = 0,
'strongly disagree' = 0)
)) |>
mutate(across(
all_of(c("EQ_4", "EQ_8", "EQ_10", "EQ_11", "EQ_12", "EQ_14", "EQ_15", "EQ_18", "EQ_21", "EQ_27", "EQ_28",
"EQ_29", "EQ_30", "EQ_31", "EQ_32", "EQ_34", "EQ_39", "EQ_46", "EQ_48", "EQ_49", "EQ_50")), # <-- added EQ_30, EQ_31
~ recode(.x,
'strongly agree' = 0,
'slightly agree' = 0,
'slightly disagree' = 1,
'strongly disagree' = 2)
)) |>
# PET
mutate(across(
starts_with("PET_"),
~ recode(.x,
'not at all' = 1,
'a little bit' = 2,
'it arouses some feelings' = 3,
'quite a lot' = 4,
'very much' = 5)
)) |>
# EYES
mutate(EYES_1 = recode(EYES_1, 'playful' = 1, .default = 0),
EYES_2 = recode(EYES_2, 'upset' = 1, .default = 0),
EYES_3 = recode(EYES_3, 'desire' = 1, .default = 0),
EYES_4 = recode(EYES_4, 'insisting' = 1, .default = 0),
EYES_5 = recode(EYES_5, 'worried' = 1, .default = 0),
EYES_6 = recode(EYES_6, 'fantasizing' = 1, .default = 0),
EYES_7 = recode(EYES_7, 'uneasy' = 1, .default = 0),
EYES_8 = recode(EYES_8, 'despondent' = 1, .default = 0),
EYES_9 = recode(EYES_9, 'preoccupied' = 1, .default = 0),
EYES_10 = recode(EYES_10, 'cautious' = 1, .default = 0),
EYES_11 = recode(EYES_11, 'regretful' = 1, .default = 0),
EYES_12 = recode(EYES_12, 'sceptical' = 1, .default = 0),
EYES_13 = recode(EYES_13, 'anticipating' = 1, .default = 0),
EYES_14 = recode(EYES_14, 'accusing' = 1, .default = 0),
EYES_15 = recode(EYES_15, 'contemplative' = 1, .default = 0),
EYES_16 = recode(EYES_16, 'thoughtful' = 1, .default = 0),
EYES_17 = recode(EYES_17, 'doubtful' = 1, .default = 0),
EYES_18 = recode(EYES_18, 'decisive' = 1, .default = 0),
EYES_19 = recode(EYES_19, 'tentative' = 1, .default = 0),
EYES_20 = recode(EYES_20, 'friendly' = 1, .default = 0),
EYES_21 = recode(EYES_21, 'fantasizing' = 1, .default = 0),
EYES_22 = recode(EYES_22, 'preoccupied' = 1, .default = 0),
EYES_23 = recode(EYES_23, 'defiant' = 1, .default = 0),
EYES_24 = recode(EYES_24, 'pensive' = 1, .default = 0),
EYES_25 = recode(EYES_25, 'interested' = 1, .default = 0),
EYES_26 = recode(EYES_26, 'hostile' = 1, .default = 0),
EYES_27 = recode(EYES_27, 'cautious' = 1, .default = 0),
EYES_28 = recode(EYES_28, 'interested' = 1, .default = 0),
EYES_29 = recode(EYES_29, 'reflective' = 1, .default = 0),
EYES_30 = recode(EYES_30, 'flirtatious' = 1, .default = 0),
EYES_31 = recode(EYES_31, 'confident' = 1, .default = 0),
EYES_32 = recode(EYES_32, 'serious' = 1, .default = 0),
EYES_33 = recode(EYES_33, 'concerned' = 1, .default = 0),
EYES_34 = recode(EYES_34, 'distrustful' = 1, .default = 0),
EYES_35 = recode(EYES_35, 'nervous' = 1, .default = 0),
EYES_36 = recode(EYES_36, 'suspicious' = 1, .default = 0)) |>
# McHugh Perspective Taking Protocol
mutate(PTP_1 = recode(PTP_1, 'Red Lego brick' = 1, .default = 0),
PTP_2 = recode(PTP_2, 'Black chair' = 1, .default = 0),
PTP_3 = recode(PTP_3, 'Watching television' = 1, .default = 0),
PTP_4 = recode(PTP_4, 'Green Lego brick' = 1, .default = 0),
PTP_5 = recode(PTP_5, 'Blue chair' = 1, .default = 0),
PTP_6 = recode(PTP_6, 'Reading' = 1, .default = 0),
#PTP_7 = recode(PTP_7, 'Black chair' = 1, .default = 0), # this item was incorrectly implemented in the survey as a single reversed trial not a double
PTP_7 = recode(PTP_7, 'Blue chair' = 1, .default = 0),
PTP_8 = recode(PTP_8, 'Black chair' = 1, .default = 0),
PTP_9 = recode(PTP_9, 'Watching television' = 1, .default = 0)) |>
# Perspective Taking Task for Adults (PTT-A) - ALL 'CORRECT' RESPONSES NEED CHECKING AGAINST JAMIE'S CODE
mutate(PTTA_1 = recode(PTTA_1, 'Picture 6' = 1, .default = 0),
PTTA_2 = recode(PTTA_2, 'Picture 4' = 1, .default = 0),
PTTA_3 = recode(PTTA_3, 'Picture 1' = 1, .default = 0),
PTTA_4 = recode(PTTA_4, 'Picture 8' = 1, .default = 0),
PTTA_5 = recode(PTTA_5, 'Picture 3' = 1, .default = 0),
PTTA_6 = recode(PTTA_6, 'Picture 2' = 1, .default = 0),
PTTA_7 = recode(PTTA_7, 'Picture 7' = 1, .default = 0),
PTTA_8 = recode(PTTA_8, 'Picture 3' = 1, .default = 0),
PTTA_9 = recode(PTTA_9, 'Picture 1' = 1, .default = 0),
PTTA_10 = recode(PTTA_10, 'Picture 2' = 1, .default = 0),
PTTA_11 = recode(PTTA_11, 'Picture 7' = 1, .default = 0),
PTTA_12 = recode(PTTA_12, 'Picture 8' = 1, .default = 0),
PTTA_13 = recode(PTTA_13, 'Picture 5' = 1, .default = 0),
PTTA_14 = recode(PTTA_14, 'Picture 6' = 1, .default = 0),
PTTA_15 = recode(PTTA_15, 'Picture 4' = 1, .default = 0),
PTTA_16 = recode(PTTA_16, 'Picture 3' = 1, .default = 0),
PTTA_17 = recode(PTTA_17, 'Picture 3' = 1, .default = 0),
PTTA_18 = recode(PTTA_18, 'Picture 6' = 1, .default = 0),
PTTA_19 = recode(PTTA_19, 'Picture 5' = 1, .default = 0),
PTTA_20 = recode(PTTA_20, 'Picture 2' = 1, .default = 0),
PTTA_21 = recode(PTTA_21, 'Picture 8' = 1, .default = 0),
PTTA_22 = recode(PTTA_22, 'Picture 1' = 1, .default = 0),
PTTA_23 = recode(PTTA_23, 'Picture 4' = 1, .default = 0),
PTTA_24 = recode(PTTA_24, 'Picture 7' = 1, .default = 0),
PTTA_25 = recode(PTTA_25, 'Picture 4' = 1, .default = 0),
PTTA_26 = recode(PTTA_26, 'Picture 5' = 1, .default = 0),
PTTA_27 = recode(PTTA_27, 'Picture 1' = 1, .default = 0), # ??
PTTA_28 = recode(PTTA_28, 'Picture 2' = 1, .default = 0), # ??
PTTA_29 = recode(PTTA_29, 'Picture 4' = 1, .default = 0), # ??
PTTA_30 = recode(PTTA_30, 'Picture 8' = 1, .default = 0), # ??
PTTA_31 = recode(PTTA_31, 'Picture 6' = 1, .default = 0), # ??
PTTA_32 = recode(PTTA_32, 'Picture 5' = 1, .default = 0)) # ??
# checks
table(data_trimmed$SITES, data_recoded$SITES)##
## 1 2 3 4 5
## 1 Not very true of me 1 0 0 0 0
## 2 0 8 0 0 0
## 3 0 0 29 0 0
## 4 0 0 0 113 0
## 5 Very true of me. 0 0 0 0 86
##
## 0 1 2 3 4
## 0 0 0 0 0
## A - DOES NOT DESCRIBE ME VERY WELL 8 0 0 0 0
## B 0 15 0 0 0
## C 0 0 47 0 0
## D 0 0 0 99 0
## E - DESCRIBES ME VERY WELL 0 0 0 0 67
##
## 0 1 2 3 4
## 0 0 0 0 0
## A - DOES NOT DESCRIBE ME VERY WELL 0 0 0 0 74
## B 0 0 0 74 0
## C 0 0 55 0 0
## D 0 25 0 0 0
## E - DESCRIBES ME VERY WELL 8 0 0 0 0
##
## 0 1 2
## 0 0 0
## slightly agree 0 104 0
## slightly disagree 19 0 0
## strongly agree 0 0 106
## strongly disagree 6 0 0
##
## 0 1 2
## 0 0 0
## slightly agree 39 0 0
## slightly disagree 0 110 0
## strongly agree 23 0 0
## strongly disagree 0 0 63
##
## 1 2 3 4 5
## 0 0 0 0 0
## a little bit 0 19 0 0 0
## it arouses some feelings 0 0 19 0 0
## not at all 4 0 0 0 0
## quite a lot 0 0 0 57 0
## very much 0 0 0 0 136
##
## 0 1
## 2 0
## arrogant 25 0
## cautious 0 168
## joking 6 0
## reassuring 36 0
##
## 0 1
## 2 0
## Black chair 47 0
## Blue chair 0 188
##
## 0 1
## 5 0
## Picture 1 13 0
## Picture 2 2 0
## Picture 3 3 0
## Picture 4 9 0
## Picture 5 1 0
## Picture 6 6 0
## Picture 7 7 0
## Picture 8 0 191
data_processed <- data_recoded |>
# SITES
mutate(SITES_completeness = ifelse(!is.na(SITES), "complete", "partial")) |>
# IRI
mutate(IRI_completeness = ifelse(rowSums(across(starts_with("IRI_"), ~ !is.na(.x))) == 28, "complete", "partial"),
IRI_FS = IRI_1 + IRI_5 + IRI_7 + IRI_12 + IRI_16 + IRI_26 + IRI_23,
IRI_EC = IRI_2 + IRI_4 + IRI_9 + IRI_14 + IRI_18 + IRI_20 + IRI_22,
IRI_PT = IRI_3 + IRI_8 + IRI_11 + IRI_15 + IRI_21 + IRI_25 + IRI_28,
IRI_PD = IRI_6 + IRI_10 + IRI_13 + IRI_17 + IRI_19 + IRI_24 + IRI_27,
IRI_total = IRI_FS + IRI_EC + IRI_PT + IRI_PD) |>
# EQ
mutate(EQ_completeness = ifelse(rowSums(across(starts_with("EQ_"), ~ !is.na(.x))) == 45, "complete", "partial"),
EQ_total = EQ_1 + EQ_4 + EQ_6 + EQ_8 + EQ_10 + EQ_11 + EQ_12 + EQ_14 + EQ_15 + EQ_18 + EQ_19 + EQ_21 + EQ_22 + EQ_25 +
EQ_26 + EQ_27 + EQ_28 + EQ_29 + EQ_32 + EQ_34 + EQ_35 + EQ_36 + EQ_37 + EQ_38 + EQ_39 + EQ_41 + EQ_42 + EQ_43 + EQ_44 +
EQ_46 + EQ_48 + EQ_49 + EQ_50 + EQ_52 + EQ_54 + EQ_55 + EQ_57 + EQ_58 + EQ_59 + EQ_60,
EQ_cog = EQ_8 + EQ_19 + EQ_22 + EQ_25 + EQ_26 + EQ_35 + EQ_36 + EQ_41 + EQ_43 + EQ_44 + EQ_52 + EQ_54 + EQ_55 + EQ_58 + EQ_60,
EQ_aff = EQ_1 + EQ_6 + EQ_18 + EQ_21 + EQ_32 + EQ_38 + EQ_39 + EQ_42 + EQ_46 + EQ_48 + EQ_50 + EQ_59,
EQ_soc = EQ_14 + EQ_29 + EQ_30 + EQ_31 + EQ_33 + EQ_34 + EQ_51 + EQ_53) |>
# PET - the mean score is calculated
mutate(PET_completeness = ifelse(rowSums(across(starts_with("PET_"), ~ !is.na(.x))) == 7, "complete", "partial"),
PET_total = (PET_1 + PET_2 + PET_3 + PET_4 + PET_5 + PET_6 + PET_7)/7) |>
# EYES
mutate(EYES_completeness = ifelse(rowSums(across(starts_with("EYES_"), ~ !is.na(.x))) == 36, "complete", "partial"),
EYES_total = EYES_1 + EYES_2 + EYES_3 + EYES_4 + EYES_5 + EYES_6 + EYES_7 + EYES_8 + EYES_9 + EYES_10 +
EYES_11 + EYES_12 + EYES_13 + EYES_14 + EYES_15 + EYES_16 + EYES_17 + EYES_18 + EYES_19 + EYES_20 +
EYES_21 + EYES_22 + EYES_23 + EYES_24 + EYES_25 + EYES_26 + EYES_27 + EYES_28 + EYES_29 + EYES_30 +
EYES_31 + EYES_32 + EYES_33 + EYES_34 + EYES_35 + EYES_36) |>
# # PTP
# mutate(PTP_completeness = ifelse(rowSums(across(starts_with("PTP_"), ~ !is.na(.x))) == 9, "complete", "partial"),
# PTP_simple = PTP_1 + PTP_2 + PTP_3,
# PTP_reversed = PTP_4 + PTP_5 + PTP_6,
# PTP_doublereversed = PTP_7 + PTP_8 + PTP_9,
# PTP_total = PTP_1 + PTP_2 + PTP_3 + PTP_4 + PTP_5 + PTP_6 + PTP_7 + PTP_8 + PTP_9) |>
# PTP
mutate(PTP_completeness = ifelse(rowSums(across(starts_with("PTP_"), ~ !is.na(.x))) == 9, "complete", "partial"),
PTP_simple = PTP_1 + PTP_2 + PTP_3,
PTP_reversed = PTP_4 + PTP_5 + PTP_6 + PTP_7, # PTP_7 was incorrectly implemented as a single reversed trial instead of double. corrected here.
PTP_doublereversed = PTP_8 + PTP_9, # PTP_7 was incorrectly implemented as a single reversed trial instead of double. corrected here.
PTP_total = PTP_1 + PTP_2 + PTP_3 + PTP_4 + PTP_5 + PTP_6 + PTP_7 + PTP_8 + PTP_9) |>
# PTT-A
# note: no completeness check as it is a timed test where not all items are answered
mutate(PTTA_total = PTTA_1 + PTTA_2 + PTTA_3 + PTTA_4 + PTTA_5 + PTTA_6 + PTTA_7 + PTTA_8 + PTTA_9 + PTTA_10 + PTTA_11 + PTTA_12 + PTTA_13 + PTTA_14 + PTTA_15 + PTTA_16 + PTTA_17 + PTTA_18 + PTTA_19 + PTTA_20 + PTTA_21 + PTTA_22 + PTTA_23 + PTTA_24 + PTTA_25 + PTTA_26 + PTTA_27 + PTTA_28 + PTTA_29 + PTTA_30 + PTTA_31 + PTTA_32) |>
# master exclude
mutate(exclude_master = ifelse(attention_check_1 == "passed" &
attention_check_2 == "passed" &
SITES_completeness == "complete" &
IRI_completeness == "complete" &
EQ_completeness == "complete" &
PET_completeness == "complete" &
EYES_completeness == "complete" &
PTP_completeness == "complete",
"include",
"exclude")) |>
# reorder
select(unique_id,
timepoint,
age, gender,
# exclusion variables
exclude_master, attention_check_1, attention_check_2, SITES_completeness, IRI_completeness, EQ_completeness, PET_completeness, EYES_completeness, PTP_completeness,
# (sub)scale scores
SITES, IRI_FS, IRI_EC, IRI_PT, IRI_PD, IRI_total, EQ_total, EQ_cog, EQ_aff, EQ_soc, PET_total, EYES_total, PTP_simple, PTP_reversed, PTP_doublereversed, PTP_total, PTTA_total,
# item level scores
IRI_1, IRI_2, IRI_3, IRI_4, IRI_5, IRI_6, IRI_7, IRI_8, IRI_9, IRI_10, IRI_11, IRI_12, IRI_13, IRI_14, IRI_15,
IRI_16, IRI_17, IRI_18, IRI_19, IRI_20, IRI_21, IRI_22, IRI_23, IRI_24, IRI_25, IRI_26, IRI_27, IRI_28,
EQ_1, EQ_4, EQ_6, EQ_8, EQ_10, EQ_11, EQ_12, EQ_14, EQ_15, EQ_18, EQ_19, EQ_21, EQ_22, EQ_25, EQ_26, EQ_27,
EQ_28, EQ_29, EQ_32, EQ_34, EQ_35, EQ_36, EQ_37, EQ_38, EQ_39, EQ_41, EQ_42, EQ_43, EQ_44, EQ_46, EQ_48, EQ_49,
EQ_50, EQ_52, EQ_54, EQ_55, EQ_57, EQ_58, EQ_59, EQ_60,
PET_1, PET_2, PET_3, PET_4, PET_5, PET_6, PET_7,
EYES_1, EYES_2, EYES_3, EYES_4, EYES_5, EYES_6, EYES_7, EYES_8, EYES_9, EYES_10, EYES_11, EYES_12, EYES_13, EYES_14,
EYES_15, EYES_16, EYES_17, EYES_18, EYES_19, EYES_20, EYES_21, EYES_22, EYES_23, EYES_24, EYES_25, EYES_26, EYES_27,
EYES_28, EYES_29, EYES_30, EYES_31, EYES_32, EYES_33, EYES_34, EYES_35, EYES_36,
PTP_1, PTP_2, PTP_3, PTP_4, PTP_5, PTP_6, PTP_7, PTP_8, PTP_9,
PTTA_1, PTTA_2, PTTA_3, PTTA_4, PTTA_5, PTTA_6, PTTA_7, PTTA_8,
PTTA_9, PTTA_10, PTTA_11, PTTA_12, PTTA_13, PTTA_14, PTTA_15, PTTA_16,
PTTA_17, PTTA_18, PTTA_19, PTTA_20, PTTA_21, PTTA_22, PTTA_23, PTTA_24,
PTTA_25, PTTA_26, PTTA_27, PTTA_28, PTTA_29, PTTA_30, PTTA_31, PTTA_32)